Kubernetes Cost Optimization

Finally, Kubernetes cost visibility that finance can read.

CoreFinOps makes Kubernetes cost allocation — per namespace, per team, per workload, per customer — a solved problem, with the automation to act on what you find.

Why Kubernetes cost is hard

A single EKS cluster can host dozens of teams. Pods move across nodes. Shared resources — load balancers, storage, control plane — don't belong to any one workload. Most cloud cost tools give up at the node level. CoreFinOps doesn't.

What CoreFinOps shows

Per-namespace cost

Complete allocation of compute, memory, storage, network, and shared infrastructure.

Per-workload cost

Cost per Deployment, StatefulSet, DaemonSet, and Job.

Per-team and per-customer cost

Roll up pod-level cost to your org hierarchy using labels and annotations.

Idle vs. active

Requested vs. used resources — the #1 source of Kubernetes waste.

Cost vs. efficiency ratios

Not just "how much does this namespace cost" but "how efficiently is it using what it pays for."

Automation for Kubernetes

Right-size workload requests and limits — recommendations based on actual pod usage, not guesses

Detect and flag orphaned resources — leftover PVCs, unused ConfigMaps, stale Jobs

Node group right-sizing — match cluster capacity to actual workload needs

Spot / preemptible adoption — identify workloads safe to run on interruptible capacity

HPA and VPA guidance — concrete autoscaler configuration based on historical patterns

Works with your stack

EKS, AKS, GKE, and self-managed Kubernetes

OpenCost-native integration (no proprietary agent)

Compatible with existing Kubecost deployments

GitOps-friendly — policy as code via Flux or ArgoCD

Prometheus-based metrics collection — no new monitoring stack

See a live Kubernetes cost breakdown.

Book a demo and we'll show CoreFinOps running against a real cluster — namespace-level allocation, rightsizing queue, and evidence log.